ArticleNucleic acids research2011
RiceXPro: a platform for monitoring gene expression in japonica rice grown under natural field conditions.
Article in Nucleic acids research, 2011. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 137 papers, 1 of them a synthesis that pooled it.
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Who cites it
137 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Meta-QTL s and haplotypes for efficient zinc biofortification of rice.The plant genome · 2023Pooled it
- OsPIP2;1 impacts root hydraulic conductance and is a candidate gene for a drought avoidance QTL on rice chromosome 7.Plant biology (Stuttgart, Germany) · 2026Article
- Evolutionary Divergence, Predicted Interaction Interface, and Regulatory Specialization of MTB as a Non-Catalytic Scaffold in the Plant m6A Writer Complex.Current issues in molecular biology · 2026Article
- OsFPN1 functions as an essential metal transporter for Fe homeostasis and Co/Ni tolerance in rice.Plant molecular biology · 2026Article
- Strawberry atlas:PeerJ · 2026Article
- Natural variation of an E3 ubiquitin ligase encoding gene Chalk9 regulates grain chalkiness in rice.Nature communications · 2025Article
- Identification and Expression Analysis of Rice MYB Family Members in Response to Heat Stress.Plants (Basel, Switzerland) · 2025Article
- Comprehensive co-expression network reveals the fine-tuning of AsHSFA2c in balancing drought tolerance and growth in oat.Communications biology · 2025Article
- Genetic dissection of root traits in a rice 'global MAGIC' population for candidate traits to breed for reduced methane emission.Frontiers in plant science · 2025Article
- Genomic regions associated with flag leaf and panicle architecture in rice (Oryza sativa L.).BMC genomics · 2024Article
- Phenotypic, Physiological, and Gene Expression Analysis for Nitrogen and Phosphorus Use Efficienies in Three Popular Genotypes of Rice (Plants (Basel, Switzerland) · 2024Article
- Genome-Wide Analysis of DNA Demethylases in Land Plants and Their Expression Pattern in Rice.Plants (Basel, Switzerland) · 2024Article
- Exploration of the pearl millet phospholipase gene family to identify potential candidates for grain quality traits.BMC genomics · 2024Article
- Defining genomic landscape for identification of potential candidate resistance genes associated with major rice diseases through MetaQTL analysis.Journal of biosciences · 2024Article
- Genome- and Transcriptome-wide Association Studies to Discover Candidate Genes for Diverse Root Phenotypes in Cultivated Rice.Rice (New York, N.Y.) · 2023Article
- Integrating omics databases for enhanced crop breeding.Journal of integrative bioinformatics · 2023Review
- Validation of Novel Reference Genes in Different Rice Plant Tissues through Mining RNA-Seq Datasets.Plants (Basel, Switzerland) · 2023Article
- A cell wall-localized cytokinin/purine riboside nucleosidase is involved in apoplastic cytokinin metabolism inProceedings of the National Academy of Sciences of the United States of America · 2023Article
- Genome-Wide Association Study Reveals the Genetic Basis of Total Flavonoid Content in Brown Rice.Genes · 2023Article
- In-silico analysis of heat shock transcription factor (OsHSF) gene family in rice (Oryza sativa L.).BMC plant biology · 2023Article
77 more citing papers are in PubMed but not listed here.
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10 authors.
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Abstract
Elucidating the function of all predicted genes in rice remains as the ultimate goal in cereal genomics in order to ensure the development of improved varieties that will sustain an expanding world population. We constructed a gene expression database (RiceXPro, URL: http://ricexpro.dna.affrc.go.jp/) to provide an overview of the transcriptional changes throughout the growth of the rice plant in the field. RiceXPro contains two data sets corresponding to spatiotemporal gene expression profiles of various organs and tissues, and continuous gene expression profiles of leaf from transplanting to harvesting. A user-friendly web interface enables the extraction of specific gene expression profiles by keyword and chromosome search, and basic data analysis, thereby providing useful information as to the organ/tissue and developmental stage specificity of expression of a particular gene. Analysis tools such as t-test, calculation of fold change and degree of correlation facilitate the comparison of expression profiles between two random samples and the prediction of function of uncharacterized genes. As a repository of expression data encompassing growth in the field, this database can provide baseline information of genes that underlie various agronomically important traits in rice.
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